I've finally made the changes to fix the scalar coercion model problems
in NumPy 1.0.1
Now, scalar coercion rules only apply when involved types are of the
same basic "kind".
Thus,
array([1,2,3],int8)*10
returns an int8 array
but
array([1,2,3],int8)*10.0
returns a float64 array.
If you want a float32 array you must use
array([1,2,3],int8)*float32(10.0)
This is actually a behavioral change which is why I asked earlier if we
should change it. However, the previous behavior was not documented
anywhere and any previous discussion on this point should have been
interpreted as the behavior now in SVN.
It's also a rare use-case and so should not create too many issues.
In running tests with NumPy and SciPy there appear to be three tests in
ndimage breaking now.
I really do want to get 1.0.2 out the door soon. What still needs to be
fixed before then?
-Travis